Development of the Second Generation NRC Acoustic Spectrum Control System for High Intensity Noise Testing
Bibliographic record
Abstract
NRC conducts high-intensity noise testing using a reverberant chamber that measures 6.9 x 9.75 x 8m. This is the only facility in Canada capable of vibroacoustic testing of full-size spacecraft and large spacecraft components at high sound pressure levels (SPL) to ensure that they withstand exposure to the intense acoustic environment during launch. Within this chamber, testing at SPLs of greater than 150dB with accurate spectrum shaping is routinely performed. From 1984 until 1993, the target acoustic spectrum for test articles was achieved through the real-time manual adjustment of 1/3-octave spectrum shapers. Over time, with ever tighter target tolerances, the ability of human operators to achieve the target spectrum over the duration of tests became severely challenged. In response, NRC developed an in-house closed-loop system for spectrum control. The key components of the first generation controller are a B&K-2131 spectrum analyzer, a Norsonic-731 noise-shaper, and a PC executing the control algorithm. Data flow between the analyzer, computer and shaper was achieved using the IEEE-488 interface. The system worked extremely well, providing accurate and reliable performance, and was used in the testing of major satellites (RADARSAT-1 and -2, and CASSIOPE amongst others). In order to eliminate the risk due to obsolescence, ageing hardware and reliance on an unsupported operating system and development environment, a plan was developed to migrate the control algorithm to a current hardware and software. After a review of available hardware and software, the National Instruments PXI platform and Labview-RT development system was chosen. A control system that provided the baseline functionality of the First Generation controller with additional features and performance was developed and benchmarked against the original system as well as two commercial acoustic control systems. A more detailed discussion of the system, along with information on its performance will be provided in the full paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".